Field of the Invention
The present invention relates to a system for optimizing air balance and excess air for a combustion process and may also be construed as a CO or combustibles tuner. The O2 is manipulated to maintain a target CO. Inclusion of the O2 balance manager and discrete logic bumps are to reduce alarms for operators. The combination of features is unique to the best of our knowledge, though inverting the treatment of O2 as a disturbance to models is different than the other vendors by itself.
Description of the Prior Art
U.S. Pat. No. 8,910,478, Dec. 16, 2014 Model-free adaptive control of supercritical circulating fluidized-bed boilers. This patent describes a multivariate control system. This is built on a family of patents starting with U.S. Pat. No. 6,055,524, Apr. 25, 2000, Model-free adaptive process control, fundamentally based on artificial neural networks to model the process and then the neural network is used as a direct or reverse acting controller. This involves connective networks to with Strong, Medium and Weak connections among several variables. While process models (per Abstract) are not required, it does require the building and maintenance of a connective mathematical representation of 5 or more signals specific to the supercritical circulating units. Often these are neural networks, but may fall under other terminology, such as connective networks, or multivariate models as used here. The patent also does not explicitly deal with O2 control or how any of the parameters may used as constraints within an optimizer.
The current invention does require the use of such techniques to predict the impact of changes in one variable upon another, although it allows a separate neural network like model to set up air conditions separate from the O2 virtual controller described in this invention. The above invention also will not respond to discrete events, as neural networks in process control are usually, if not always, limited to smooth continuous functions, as neural network math does not had step changes well.
U.S. Pat. No. 7,756,591. Jul. 13, 2010, system for optimizing oxygen in a boiler. This patent describes the use of a predictive model to control the O2. This is similar to the U.S. Pat. No. 6,055,524 family of patents above; though this tracks its pedigree to U.S. Pat. No. 5,167,009 which describe the general use of neural networks for process control. This adds the concept of using the O2 model in an optimizer to determine the O2 as part of the overall system optimization. This invention does not predict the O2, but instead uses indications of combustion efficiency to adjust the O2 values in a feedback loop in real-time. O2 is not optimized through a model—optimizer combination but instead is set up to control the excess air to maintain a target value or target range value for carbon monoxide (or other combustion byproduct indications).
U.S. Pat. No. 6,739,122, May 25, 2004. Air-fuel ratio feedback control apparatus. This patent describes an adaptive controller that uses feedback on NOx values. The description includes the use of O2 in a dynamic gain use. However, a major difference is the specific application of the engine exhaust system (car, truck, etc) and the need for O2 sensors before and after the catalyst. Further, the patent does not include the use of CO for efficiency feedback nor include any discrete logic.